Improved forecasting at StateFleet driven by SAS®
Managing 25,000 vehicles is a major and complex challenge for StateFleet, the fleet leasing organisation for the New South Wales state Government, Australia. But with SAS, StateFleet can run forecasts within minutes that used to take a week – and with greater accuracy.
StateFleet operates one of the largest motor-vehicle fleets in Australia and provides a complete range of fleet services, including leasing, fleet and pool management; vehicle rental; and accident management.
The NSW Government is committed to efficient resource management, so agencies such as StateFleet must implement effective motor-vehicle and management procedures.
SAS gives us the ability to continue to enhance our offerings to our clients and allows us to deliver a much more robust solution where clients are able to carry out data mining in an easy and efficient manner.
And that's a complex task. StateFleet has more than 100 customers, and its fleet is valued at about AUD$700 million (US$723.8 million). Each year, State Fleet adds another 8,000 vehicles.
To help manage resources efficiently, StateFleet has been using solutions from SAS.
Initially, StateFleet implemented SAS Business Intelligence to assist with the secure reporting needs of its head office and clients. But StateFleet Executive Director Michael Wright says the organisation has since upgraded to the latest version of SAS Enterprise BI Server, which offers online reporting and analysis for its clients.
More than 800 reports are generated every day, and Wright says the upgrade has been well received by clients, especially for the greater flexibility it provides.
"The new version confirms what a powerful tool SAS is for analysis and forecasting," Wright says. "We refresh the data every night in the SAS database, and reports are available as soon as the data is loaded. So, at the most, data is never any more than 24 hours old."
The solution is also used to help predict the resale value of vehicles once they reach the end of their lease. The value is used to determine the leasing costs for clients, so coming up with an accurate figure is critical for cost control. Wright says even a 1 percent error across the board in residual prediction could result in a $3 million deficit.
"The predictive analysis and data cleansing capabilities are very important to us," he says. "If too many of one make of vehicle were coming back onto the market at one time, the resale value could reduce by as much as $2,000 per vehicle; therefore accurate reporting is a major advantage for us."
SAS® provides greater flexibility
StateFleet clients use SAS to conduct in-depth analysis of their fleets and obtain information relating to issues such as maintenance costs, vehicle use and fuel use. With the introduction of a new fleet management system, StateFleet can now provide its clients with more options, such as access to improved data mining and analysis around assets to help them manage their costs more effectively.
"Clients can now report items that are specific to their own needs," Wright says. "This could be geographic information depending on where they are based or relating to their individual assets. They can also manipulate the data to produce the type of report they need for their current task."
Wright says the new version of SAS provides better functionality. "Clients can produce reports in a customised view called 'My Reports,' which gives them greater functionality," he says. "They can create their own personalised reports as opposed to just producing a standardised one. They can then save these reports in their own reports folder. Many of these reports are used by clients on a daily basis, so it is critical the data is as up-to-date as possible."
Forecasting helps plan for future costs
StateFleet is having great success using SAS for forecasting. Wright says a comprehensive forecasting program is being rolled out over a five-year period.
"The first stage is already helping us with forecasting our capital requirements," Wright says. "One area where we are finding it extremely useful is in helping us calculate new minimum leasing-term packages by looking at existing lease arrangements and when they expire."
Wright explains that a leasing term is generally for three years, but StateFleet wanted to see how its capital requirements would be affected if the terms were changed to reflect different periods.
"We apply the SAS forecasting model to forecast events such as how our capital requirements would change for the different terms," he says. "For example, if we move from a three-year, 60,000 kilometre arrangement to a four-year, 80,000 kilometre arrangement, we can see instantly what our capital projections would be."
Wright says the results can be seen immediately by changing the variables. Before SAS, this same type of forecast used to require a week's work.
"Over the next five years, we will be adding further enhancements that assist us with forecasting items such as net capital requirements, profit and loss, and revenue," Wright says.
Another key factor with StateFleet's latest SAS implementation is the ability for role-based reporting as opposed to blanket-based reporting.
Wright says StateFleet has additional plans for SAS. As more organisations move into cloud computing, he foresees the potential to bring other users into the SAS system, with StateFleet acting as an information service provider for them.
"These users could be other state governments that have government fleets that are similar to ours, where they have the same reports and a separate database," Wright says. "There are also procurement and data mining opportunities and a number of other applications we can explore."
Wright says the SAS implementation has been very successful; he particularly likes how stable and robust it is.
"We know that we still haven't plumbed the depths of what SAS can offer us and what we are able to do with it," he says. "SAS gives us the ability to continue to enhance our offerings to our clients and allows us to deliver a much more robust solution where clients are able to carry out data mining in an easy and efficient manner. We have lots more to discover with SAS."
Forecast future capital requirements for more accurate cost predictions; provide clients with an improved reporting and budgeting solution.
Capital requirements for different lease arrangements are available immediately, a process that used to take a week; clients can customise reports based on individual circumstances and job roles.